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To overcome these limitations, we present NarrativeSense, a novel framework that combines machine learning models with narrative-based descriptions of daily life events inferred from smartphone sensing data to predict weekly affective states. The system incorporates language model components to transform behavioral patterns into contextualized, human-readable narratives that ground affective predictions in everyday experiences. This narrative layer complements structured prediction by offering intuitive, user-centered insights. Applied to longitudinal data from 58 university students over 119\u2009days, NarrativeSense outperforms baseline machine learning models, standalone LLMs, and ensemble methods, while providing richer insights. Our findings demonstrate the potential of narrative-enhanced digital phenotyping for scalable and explainable mental health monitoring in educational and clinical settings.<\/jats:p>","DOI":"10.1145\/3788688","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T14:37:56Z","timestamp":1768833476000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["NarrativeSense: Predicting Affective States in University Students through Smartphone Sensing and Contextual Narratives"],"prefix":"10.1145","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0778-8844","authenticated-orcid":false,"given":"Tianyi","family":"Zhang","sequence":"first","affiliation":[{"name":"The University of Melbourne, Melbourne, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-4561-465X","authenticated-orcid":false,"given":"Yan","family":"Li","sequence":"additional","affiliation":[{"name":"The University of Sydney, Sydney, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5065-6911","authenticated-orcid":false,"given":"Yihao","family":"Ding","sequence":"additional","affiliation":[{"name":"The University of Western Australia, Perth, Australia and The University of Sydney, Sydney, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6047-4158","authenticated-orcid":false,"given":"Hong","family":"Jia","sequence":"additional","affiliation":[{"name":"The University of Auckland, Auckland, New Zealand and The University of Melbourne, Melbourne, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2804-6038","authenticated-orcid":false,"given":"Vassilis","family":"Kostakos","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Melbourne, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7407-8730","authenticated-orcid":false,"given":"Simon","family":"D\u2019Alfonso","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Melbourne, Australia"}]}],"member":"320","published-online":{"date-parts":[[2026,3,17]]},"reference":[{"issue":"1","key":"e_1_3_1_2_2","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.jad.2006.05.003","article-title":"Student anxiety and depression: Comparison of questionnaire and interview assessments","volume":"95","author":"Andrews Bernice","year":"2006","unstructured":"Bernice Andrews, Jennie Hejdenberg, and John Wilding. 2006. 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